The quality of a video image is ultimately determined by a human viewer of video image. Video noise includes significant energy (i.e., a significant number of bits) that does not contribute to the quality of the video image as determined by the human viewer of the video image. Video images containing video noise and difficult-to-track visual details are known to be determined to be of similar quality to similar video images without the video noise and difficult-to-track visual details. Thus, compression of video images for transmission or storage is impacted by both the video noise and the difficult-to-track visual details.
Reducing the energy or entropy of the video noise and difficult-to-track visual details will reduce the number of bits required to code video. However, it is difficult to accurately identify video noise and to accurately identify difficult-to-track visual details. In addition, if important details in the video image are removed, the end user will perceive a degradation in video quality. This degradation is known to include effects such as perceptual masking, in which interference from one perceptual stimulus decreases perceptual effectiveness of other perceptual stimulus.